Abstract
Glaciers calving icebergs into the ocean significantly contribute to sea-level rise and can trigger tsunamis, posing severe hazards for coastal regions. Computational modeling of such multiphase processes is a great challenge involving complex solid–fluid interactions. Here, a new continuum damage Material Point Method has been developed to model dynamic glacier fracture under the combined effects of gravity and buoyancy, as well as the subsequent propagation of tsunami-like waves induced by released icebergs. We reproduce the main features of tsunamis obtained in laboratory experiments as well as calving characteristics, the iceberg size, tsunami amplitude and wave speed measured at Eqip Sermia, an ocean-terminating outlet glacier of the Greenland ice sheet. Our hybrid approach constitutes important progress towards the modeling of solid–fluid interactions, and has the potential to contribute to refining empirical calving laws used in large-scale earth-system models as well as to improve hazard assessments and mitigation measures in coastal regions, which is essential in the context of climate change.
Highlights
Glaciers calving icebergs into the ocean significantly contribute to sea-level rise and can trigger tsunamis, posing severe hazards for coastal regions
To model the dynamic fracture of the glacier ice, we developed a non-associative elastoplastic model based on the Cohesive Cam Clay (CCC) yield surface used by Gaume et al.[27] to simulate snow and avalanche mechanics
In a first set of experiments, we model the tsunami wave response to three main calving mechanisms according to the laboratory experiments of Heller et al.[13]: (i) gravity-dominated fall (GF), (ii) buoyancy-dominated fall (BF), and (iii) capsizing (CS)
Summary
Glaciers calving icebergs into the ocean significantly contribute to sea-level rise and can trigger tsunamis, posing severe hazards for coastal regions. Computational modeling of such multiphase processes is a great challenge involving complex solid–fluid interactions. Glacier calving into the ocean (Fig. 1) is predicted to be one of the largest contributions to sea-level rise in the future[1,2,3]. This process corresponds to ~50% of the mass loss from ice sheets in Greenland and Antarctica[4,5]. The discrete nature of these models makes them computationally very expensive and limited to single events
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